Commemorating the Deceased: Chinese Literati Memorial Painting - A Case Study of Wu Li's "Remembering the Past at Xingfu Chapel" (1672)

Despite an increasing amount of research on commemorative paintings, Chinese paintings by educated scholars to commemorate the deceased have rarely been studied. This dissertation provides a series of case studies of Chinese literati memorial paintings to explore their visual representations in social and religious contexts. It shows how, and why, the first literati memorial paintings appeared in the Wu (i.e. Suzhou) area in Jiangsu province by the end of the 15th century, and flourished in the late Ming and early Qing periods, when secret messages were encoded in visual representations, either due to fear of political punishment or for religious and personal reasons. A representative in-depth case study is the painting Remembering the Past at Xingfu Chapel (Xingfu an ganjiu tu) by the Christian painter Wu Li (1632-1718) in 1672 for his deceased Buddhist monk friend Morong (?-1671) for having a good Buddhist afterlife and a three-year-soul-journey. This case study identifies the symbolic meanings of visual images in the seemingly innocuous landscape painting and shows how secret messages were encoded in religious allusions. This dissertation uncovers a new and important genre in Chinese painting and reveals the intellectual and religious inner-world of scholars and painters in the Ming and Early Qing China

Topological energy gaps in the [111]-oriented InAs/GaSb and GaSb/InAs core-shell nanowires

The [111]-oriented InAs/GaSb and GaSb/InAs core-shell nanowires have been studied by the $8\times 8$ Luttinger-Kohn $\vec{k}\cdot\vec{p}$ Hamiltonian to search for non-vanishing fundamental gaps between inverted electron and hole bands. We focus on the variations of the topologically nontrivial fundamental gap, the hybridization gap, and the effective gap with the core radius and shell thickness of the nanowires. The evolutions of all the energy gaps with the structural parameters are shown to be dominantly governed by quantum size effects. With a fixed core radius, a topologically nontrivial fundamental gap exists only at intermediate shell thicknesses. The maximum gap is $\sim 4.4$ meV for GaSb/InAs and $\sim 3.5$ meV for InAs/GaSb core-shell nanowires, and for the GaSb/InAs core-shell nanowires the gap persists over a wider range of geometrical parameters. The intrinsic reason for these differences between the two types of nanowires is that in the shell the electron-like states of InAs is more delocalized than the hole-like state of GaSb, while in the core the hole-like state of GaSb is more delocalized than the electron-like state of InAs, and both features favor stronger electron-hole hybridization. Since similar features of the electron- and hole-like states have been found in nanowires of other materials, it could serve as a common rule to put the hole-like state in the core while the electron-like state in the shell of a core-shell nanowire to achieve better topological properties.Comment: 10 pages, 10 figure

Artificial Neural Network Prediction of COVID-19 Daily Infection Count

It is well known that the confirmed COVID-19 infection is only a fraction of the true fraction. In this paper we use an artificial neural network to learn the connection between the confirmed infection count, the testing data, and the true infection count. The true infection count in the training set is obtained by backcasting from the death count and the infection fatality ratio (IFR). Multiple factors are taken into consideration in the estimation of IFR. We also calibrate the recovered true COVID-19 case count with an SEIR model

Evaluating Similitude and Robustness of Deep Image Denoising Models via Adversarial Attack

Deep neural networks (DNNs) have a wide range of applications in the field of image denoising, and they are superior to traditional image denoising. However, DNNs inevitably show vulnerability, which is the weak robustness in the face of adversarial attacks. In this paper, we find some similitudes between existing deep image denoising methods, as they are consistently fooled by adversarial attacks. First, denoising-PGD is proposed which is a denoising model full adversarial method. The current mainstream non-blind denoising models (DnCNN, FFDNet, ECNDNet, BRDNet), blind denoising models (DnCNN-B, Noise2Noise, RDDCNN-B, FAN), and plug-and-play (DPIR, CurvPnP) and unfolding denoising models (DeamNet) applied to grayscale and color images can be attacked by the same set of methods. Second, since the transferability of denoising-PGD is prominent in the image denoising task, we design experiments to explore the characteristic of the latent under the transferability. We correlate transferability with similitude and conclude that the deep image denoising models have high similitude. Third, we investigate the characteristic of the adversarial space and use adversarial training to complement the vulnerability of deep image denoising to adversarial attacks on image denoising. Finally, we constrain this adversarial attack method and propose the L2-denoising-PGD image denoising adversarial attack method that maintains the Gaussian distribution. Moreover, the model-driven image denoising BM3D shows some resistance in the face of adversarial attacks.Comment: 12 pages, 15 figure

Commanding Wheelchair in Virtual Reality with Thoughts by Multiclass BCI based on Movement-related Cortical Potentials

Brain-driven wheelchair control is an attractive application in theBrain-Computer Interface (BCI) field. In this research, wedesigned and validated a virtual wheelchair navigation systemcontrolled by our latest multiclass BCI Menu interface based on afast brain switch, which provides five commands: move forward,turn left, turn right, move backward, and stop. Preliminary resultshave shown that subjects can successfully control the wheelchairto hit all targets in the immersive virtual reality (VR)environment. This system proves an avenue to bridge the gapbetween simulation control in VR environments and real-lifewheelchair applications for mobility impairment